https://github.com/mycielski/textract_study

Analysing expense reports/invoices with AWS Textract and boto3.
https://github.com/mycielski/textract_study

aws aws-cli boto3 document-understanding expenses invoices script shell textract

Last synced: 29 days ago
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Analysing expense reports/invoices with AWS Textract and boto3.

• Host: GitHub
• URL: https://github.com/mycielski/textract_study
• Owner: mycielski
• Created: 2023-11-21T16:13:30.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-11-27T01:35:37.000Z (over 2 years ago)
• Last Synced: 2025-02-23T18:47:13.398Z (over 1 year ago)
• Topics: aws, aws-cli, boto3, document-understanding, expenses, invoices, script, shell, textract
• Language: Python
• Homepage:
• Size: 25.4 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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README

          
# AWS Textract study

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

Some code I've written when learning what is Textract and how to use it.

The project also contains a shell script which uses the AWS CLI v2 to perform the same task.

## How to use it?

1. Put your invoices in the `demo_data` directory.

   Here's an example of the directory structure:

    ```sh

    .

    ├── demo_data

    │   ├── invoice.pdf

    │   └── invoices

    │       ├── other_invoice.jpg

    │       └── and_one_more_invoice.png

    ├── readme.md

    └── src

        └── main.py

    ```

2. Provide your AWS credentials as environment variables:

    ```sh

    $ export AWS_ACCESS_KEY_ID=your_access_key_id          # for example "AKIAIOSFODNN7EXAMPLE"

    $ export AWS_SECRET_ACCESS_KEY=your_secret_access_key  # for example "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"

    $ export AWS_REGION=region                             # for example "us-east-1"

    $ export AWS_BUCKET=bucket_name                        # for example "my-textract-study-bucket"

    ```

3. Run the script:

    ```sh

    $ python src/main.py

    ```

4. The report will be generated with a name like `.xlsx`:

    ```sh

    .

    ├── demo_data

    │   ├── invoice.pdf

    │   └── invoices

    │       ├── other_invoice.jpg

    │       └── and_one_more_invoice.png

    ├── output

    │   └── 456af71d-f7b2-4bf8-87c7-bade21d843d4

    │       ├── report.csv

    │       ├── report.json

    │       └── report.xlsx

    ├── readme.md

    └── src

        └── main.py

    ```

## Notes

- This script uses busy waiting for Textract job results (in the `retrieve_analyses` function). It is not optimal. In fact, it is pretty terrible for performance. Use [notifications](https://docs.aws.amazon.com/textract/latest/dg/api-async.html#:~:text=The%20completion%20status%20of%20the%20request%20is%20published%20to%20an%20Amazon%20Simple%20Notification%20Service%20(Amazon%20SNS)%20topic.) instead.

- The whole thing is just one file. Terrible for legibility but eh, it works.