Skip to main content

Import unstructured data (text and images) into structured tables

Project description

datasette-extract

PyPI Changelog Tests License

Import unstructured data (text and images) into structured tables

Installation

Install this plugin in the same environment as Datasette.

datasette install datasette-extract

Configuration

This plugin requires an OPENAI_API_KEY environment variable with an OpenAI API key.

Usage

This plugin provides the following features:

  • In the database action cog menu for a database select "Create table with extracted data" to create a new table with data extracted from text or an image
  • In the table action cog menu select "Extract data into this table" to extract data into an existing table

When creating a table you can specify the column names, types and provide an optional hint (like "YYYY-MM-DD" for dates) to influence how the data should be extracted.

When populating an existing table you can provide hints and select which columns should be populated.

Text input can be pasted directly into the textarea.

Drag and drop a PDF or text file onto the textarea to populate it with the contents of that file. PDF files will have their text extracted, but only if the file contains text as opposed to scanned images.

Drag and drop a single image onto the textarea - or select it with the image file input box - to process an image. These will have OCR run against them using GPT-4 Vision and then that text will be used for structured data extraction.

Permissions

Users must have the datasette-extract permission to use this tool.

In order to create tables they also need the create-table permission.

To insert rows into an existing table they need insert-row.

Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

cd datasette-extract
python3 -m venv venv
source venv/bin/activate

Now install the dependencies and test dependencies:

pip install -e '.[test]'

To run the tests:

pytest

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

datasette-extract-0.1a2.tar.gz (806.2 kB view details)

Uploaded Source

Built Distribution

datasette_extract-0.1a2-py3-none-any.whl (815.1 kB view details)

Uploaded Python 3

File details

Details for the file datasette-extract-0.1a2.tar.gz.

File metadata

  • Download URL: datasette-extract-0.1a2.tar.gz
  • Upload date:
  • Size: 806.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for datasette-extract-0.1a2.tar.gz
Algorithm Hash digest
SHA256 4b5857af9ffbe08be061404e19cf135d498138aed355d382578bf819e3f09002
MD5 dde6a1343a945005c8b2b6de5fd6b4bd
BLAKE2b-256 1add3025cbcd1e385f37819cf967e3c692321a070b6291da8567bca7ab8a8493

See more details on using hashes here.

File details

Details for the file datasette_extract-0.1a2-py3-none-any.whl.

File metadata

File hashes

Hashes for datasette_extract-0.1a2-py3-none-any.whl
Algorithm Hash digest
SHA256 00bee692c548c9ae08c2cf769b35bc4dea253d924453ff08dd191f371baa46ad
MD5 ee1d6bb2a9f5b4fbd0065c6d7561c04a
BLAKE2b-256 9814ccf7e98e221a8f0eae2f7d059a10426a7ab93eee5e91b494c05234727e03

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page