patent-client 2.0.1

A set of ORM-style clients for publicly available intellectual property data

Overview

A set of Django-ORM-Style accessors to publicly available intellectual property data.

Currently supports:

• European Patent Office - Open Patent Services

  • Inpadoc - Full Support

  • EPO Register - Full Support

  • Classification - No Support

• United States Patent & Trademark Office

  • Patent Examination Data - Full Support

  • Patent Assignment Data - Lookup Support

  • Patent Trial & Appeal Board API - Full Support

• United States International Trade Commission

  • Electronic Document Information System (EDIS) API - Full Support

• Free software: Apache Software License 2.0

Installation

pip install patent_client

If you only want access to USPTO resources, you’re done! However, additional setup is necessary to access EPO Inpadoc and EPO Register resources. See the Docs.

Documentation

The easiest way to get started is with Patent Client Examples. The examples repository has a list of Jupyter notebooks showing application examples of the patent_client library.

Docs, including a fulsome Getting Started are available on Read the Docs.

SUPER QUICK START

To use the project:

# Import the model classes you need
>>> from patent_client import Inpadoc, Epo, Assignment, USApplication

# Fetch US Applications
>>> app = USApplication.objects.get('15710770')
>>> app.patent_title
'Camera Assembly with Concave-Shaped Front Face'

# Fetch from USPTO Assignments
>>> assignments = Assignment.objects.filter(assignee='Google')
>>> len(assignments)
23860
>>> assignments[0].id
'47086-788'
>>> assignments[0].conveyance_text
'ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS).'

# Fetch from INPADOC
>>> pub = Inpadoc.objects.get('EP3082535A1')
>>> pub.title
'AUTOMATIC FLUID DISPENSER'
>>> pub.priority_claims
['201314137130', '2014071849']

# Fetch from EPO Register
>>> epo = Epo.objects.get('EP3082535A1')
>>> epo.title
'AUTOMATIC FLUID DISPENSER'
>>> epo.status
[{'description': 'Examination is in progress', 'code': '14', 'date': '20180615'}]

Other Languages

Merely as a way to explore other languages and technologies, I have built a few (partial) ports of this library to other languages:

• patent_client_js - ES6 Javascript (PEDS / PTAB / Assignments support (ASYNC!))

• patent_client_java - Java (Ptab API only)

• patent_client_scala - Scala (Ptab API only)

• patent_client_ruby - Ruby (Nothing Works Yet)

Development

To run the all tests run:

pytest

A developer guide is provided in the Documentation. This project is narrowly scoped to only public documented API’s available without charge (at least for moderate usage). Scrapers of HTML websites are not permitted. But PR’s to add support for new API’s are more than welcome.

Pull requests welcome!

Related projects

• Python EPO OPS Client

• Google Public Patent Data

Changelog

2.0.1 (2020-03-12)

• Fixed problem where Inpadoc was indexing improperly

2.0.0 (2020-03-11)

• Major update with breaking API changes

• Refactored all API’s to use requests_cache rather than custom caching scheme

• Uses Marshmallow for data validation, and memory-efficient dataclasses for all objects

• As part of the above, all API’s now re-use the same requests.Session() object

• Deleted a ton of unnecessary code (Deleted code == debugged code)

• NOTE: Documentation not yet up-to-date. That is the next project

0.4.0 (2019-01-30)

• Renewed commitment to adhere to semantic versioning

• Added several new synthetic data attributes, including expiration date calculations

• General updates and improvements, including an overhaul of the base Manager and Model classes

0.2.3 (2018-11-02)

• Added parser for Inpadoc claims so they have an object repesentation

0.1.5 (2018-10-25)

• Massive refactor of OPS client

0.1.4 (2018-10-24)

• Support for USPTO Applications, Assignments, and PTAB documents

• Support for EPO Inpadoc and EPO Register

• Initial Installation and Getting Started Documentation

0.0.1 (2018-10-15)

• First release on PyPI.

• Support for EPO OPS (except Classification data)