Skip to main content

An API wrapper for Springer Nature

Project description

sprynger

Simple API wrapper for the Springer Nature APIs.

PyPI version Python versions Documentation Status Downloads License Maintainability

🏔️ Overview Springer Nature

Springer Nature currently offers three APIs:

  • Springer Metadata API: Metadata of articles, journal articles and book chapters.
  • Springer Meta API: Advanced version offering versioned metadata.
  • Springer OpenAccess API: Metadata and, where available, full-text

Note: sprynger currently supports the Metadata and OpenAccess API

⬇️ Install

Download and install the package from PyPI:

pip install sprynger

🪧 Example Use

Metadata

from sprynger import Metadata, init

init()

book_metadata = Metadata(isbn='978-3-031-63497-0', nr_results=3)
for chapter in book_metadata:
    print(chapter.identifier)
    print(chapter.abstract)

doi:10.1007/978-3-031-63498-7_20

Modern solvers for quantified Boolean formulas (QBFs) process formulas in prenex form, ...

doi:10.1007/978-3-031-63498-7_9

Given a finite consistent set of ground literals, we present an algorithm that generates ...

doi:10.1007/978-3-031-63498-7_3

The TPTP World is a well established infrastructure that supports research, development, ...

book_metadata.facets

[MetadataFacets(facet='subject', value='Artificial Intelligence', count='27'),...]

OpenAccess

from sprynger import OpenAccess
results = OpenAccess('"quantum computing"',
                     dateto='2022-12-30',
                     type='Journal Article',
                     nr_results=3)
results.documents_found

4350

for document in results:
    print(document.title)
    print(document.paragraphs[0].text)

A neural network assisted

A versatile magnetometer must deliver a readable response when exposed to target fields ...

Experimental demonstration of classical analogous time-dependent superposition of states

One of the quantum theory concepts on which quantum information processing stands is superposition ...

A quantum-like cognitive approach to modeling human biased selection behavior

Cognitive biases of the human mind significantly influence the human decision-making process ...

📖 Documentation

For a comprehensive guide, see the documentation in read the docs.

⭐️ Give the package a star

If the package helped you, give it a star!

⚠️ Disclaimer

This project is an independent API wrapper for the Springer Nature API. It is not affiliated with, endorsed, or maintained by Springer Nature. For official support, please refer to the Springers's documentation and support channels.

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

sprynger-0.0.2.tar.gz (20.2 kB view hashes)

Uploaded Source

Built Distribution

sprynger-0.0.2-py3-none-any.whl (23.9 kB view hashes)

Uploaded Python 3

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