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Open source document management system for digital archives

Project description

Tests

Papermerge REST API Server

This python package is the heart of Papermerge project. It consists of a set of reusable Django apps which are consumed across different bundles of Papermerge Document Management System (DMS).

Technically speaking, it contains following Django apps:

  • papermerge.core - the epicenter of Papermerge DMS project
  • papermerge.notifications - Django Channels app for sending notifications via websockets
  • papermerge.search - RESTful search. Supports four backends: Xapian, Whoosh, Elasticsearch, Solr.

What is Papermerge?

Papermerge is an open source document management system (DMS) primarily designed for archiving and retrieving your digital documents. Instead of having piles of paper documents all over your desk, office or drawers - you can quickly scan them and configure your scanner to directly upload to Papermerge DMS. Papermerge DMS on its turn will extract text data from the scanned documents using Optical Character Recognition (OCR) technology the index it and make it searchable. You will be able to quickly find any (scanned!) document using full text search capabilities.

Papermerge is perfect tool to manage documents in PDF, JPEG, TIFF and PNG formats.

Features Highlights

  • OpenAPI compliant REST API
  • Works well with PDF documents
  • OCR (Optical Character Recognition) of the documents (uses OCRmyPDF)
  • Full Text Search of the scanned documents (supports four search engine backends, uses Xapian by default)
  • Document Versions
  • Tags - assign colored tags to documents or folders
  • Documents and Folders - users can organize documents in folders
  • Multi-User (supports user groups)
  • User permissions management
  • Page Management - delete, reorder, cut & paste pages (uses PikePDF)

Documentation

For an overview on REST API is available here.

Detailed online REST API reference can be viewed as:

Note that REST API reference documentation is generated from OpenAPI schema. OpenAPI schema is stored in its own dedicated repository papermerge/openapi-schema.

Papermerge DMS documentation is available at https://docs.papermerge.io

Docker

In order to start Papermerge REST API server as docker image use following command:

docker run -p 8000:8000 \
    -e PAPERMERGE__MAIN__SECRET_KEY=abc \
    -e DJANGO_SUPERUSER_PASSWORD=123 \
    papermerge/papermerge:latest

If you want initial superuser to have another username (e.g. john), use DJANGO_SUPERUSER_USERNAME environment variable:

docker run -p 8000:8000 \
    -e PAPERMERGE__MAIN__SECRET_KEY=abc \
    -e DJANGO_SUPERUSER_PASSWORD=123 \
    -e DJANGO_SUPERUSER_USERNAME=john \
    papermerge/papermerge:latest

For full list of supported environment variables check online documentation.

Docker Compose

By default Papermerge REST API server uses sqlite3 database. In order to use PostgreSQL use following docker compose file:

version: '3.7'
services:
  app:
    image: papermerge/papermerge
    environment:
      - PAPERMERGE__MAIN__SECRET_KEY=abc
      - DJANGO_SUPERUSER_PASSWORD=12345
      - PAPERMERGE__DATABASE__TYPE=postgres
      - PAPERMERGE__DATABASE__USER=postgres
      - PAPERMERGE__DATABASE__PASSWORD=123
      - PAPERMERGE__DATABASE__NAME=postgres
      - PAPERMERGE__DATABASE__HOST=db
    ports:
      - 8000:8000
    depends_on:
      - db
  db:
    image: bitnami/postgresql:14.4.0
    volumes:
      - postgres_data:/var/lib/postgresql/data/
    environment:
      - POSTGRES_PASSWORD=123
volumes:
    postgres_data:version: '3.7'

Above mentioned docker compose file can be used to start Papermerge REST API server which will use PostgreSQL database to store data.

For detailed description on how to start Papermerge DMS using docker compose read Docker Compose/Detailed Explanation section in online docs.

Tests

Test suite is divided into two big groups:

  1. tests.core
  2. tests.search

First group is concerned with tests which do not depend on elasticsearch while second one tests.search is concerned with tests for which depend on elasticsearch and as result run very slow (hence the grouping). In order to run tests.core tests you need to have redis up and running; in order to run test.search you need to both redis and elasticsearch up and running.

Before running core tests suite, make sure redis service is up and running. Run tests:

 poetry run task test-core

Before running search tests suite, make sure both redis and elasticsearch services are up and running:

 poetry run task test-search

In order to run all tests suite (core + search):

poetry run task test

Linting

Use following command to make sure that your code is formatted per PEP8 spec:

poetry run task lint

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