<h2 align="center">RESP: Research Papers Search</h2> <h4 align="center">Fetch academic research papers from multiple sources including Google Scholar, Arxiv, Semantic Scholar, ACL, ACM, and more</h4> <p align="center"> <a href="https://pypi.org/project/respsearch/"><img src="https://img.shields.io/pypi/v/respsearch.svg" alt="PyPI version"></a> <a href="https://pypi.org/project/respsearch/"><img src="https://img.shields.io/pypi/pyversions/respsearch.svg" alt="Python versions"></a> <a href="https://opensource.org/licenses/Apache-2.0"><img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg" alt="License"></a> <a href="https://github.com/monk1337/resp/commits/main"><img src="https://img.shields.io/github/last-commit/monk1337/resp" alt="GitHub commit"></a> <a href="http://makeapullrequest.com"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square" alt="PRs Welcome"></a> <a href="https://colab.research.google.com/drive/188cWcZrBRVGAF3Dp_5uswmLgbBNKSioB?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> </p>

Installation

pip install respsearch

For Connected Papers support (requires Selenium):

pip install respsearch[selenium]

Quick Start

Simple API (Recommended)

from resp import arxiv, semantic_scholar, acm, google_scholar

# Arxiv - No API key needed
papers = arxiv.search_papers("deep learning", max_results=10)

# Semantic Scholar - No API key needed
papers = semantic_scholar.search_papers("natural language processing", max_results=5)

# ACM Digital Library - No API key needed
papers = acm.search_papers("machine learning", max_results=5)

# Google Scholar - Requires free SerpAPI key from https://serpapi.com/
google_scholar.set_api_key("your_serpapi_key")
papers = google_scholar.search_papers("machine learning", num_results=10)

Advanced API (Direct Class Access)

from resp.apis.arxiv_api import Arxiv
from resp.apis.semantic_s import Semantic_Scholar
from resp.apis.serp_api import Serp

# Arxiv
ap = Arxiv()
papers = ap.arxiv('deep learning', max_pages=5)

# Semantic Scholar
sc = Semantic_Scholar()
papers = sc.ss('neural networks', max_pages=3)

# Google Scholar via Serp
serp = Serp(api_key="your_serpapi_key")
papers = serp.google_scholar_search('transformers', max_pages=2)

Features

🔍 Search papers by keywords across multiple academic sources
📚 Fetch citations of any paper from Google Scholar
🔗 Find related papers from Google Scholar
🕸️ Connected Papers - discover papers using similarity graphs (not just citations)

Supported Sources

| Source | API Key Required | Status | |--------|------------------|--------| | Arxiv | ✅ Free | ✅ Working | | Semantic Scholar | ✅ Free | ✅ Working | | Google Scholar | 🔑 Required (SerpAPI) | ✅ Working | | ACM Digital Library | ✅ Free | ⚠️ Limited* | | ACL Anthology | ✅ Free | ✅ Via Resp | | PMLR | ✅ Free | ✅ Via Resp | | NeurIPS | ✅ Free | ✅ Via Resp | | IJCAI | ✅ Free | ✅ Via Resp | | OpenReview | ✅ Free | ✅ Via Resp | | CVF Open Access | ✅ Free | ✅ Via Resp | | Connected Papers | ✅ Free | ✅ Requires Selenium |

<sub>*ACM website structure changes frequently, may return limited results</sub>

Advanced Features

Google Scholar: Get Citations & Related Papers

from resp import google_scholar

# Set API key once
google_scholar.set_api_key("your_serpapi_key")

# Search papers
papers = google_scholar.search_papers("attention mechanism", num_results=5)

# Get citations for a paper
citations = google_scholar.get_citations("Attention is all you need")

# Get related papers
related = google_scholar.get_related_papers("BERT language model")

Connected Papers (Requires Selenium)

from resp import connected_papers

# Install first: pip install respsearch[selenium]
papers = connected_papers().get_connected_papers("paper_title")

Using Resp Class for Multiple Sources

from resp import Resp

# Search across ACL, PMLR, NeurIPS, etc.
resp = Resp()
papers = resp.search_papers("keyword", source="acl")

Citation

If you find this repository useful, please cite:

@misc{Resp2021,
  title = {RESP: Research Papers Search},
  author = {Pal, Ankit},
  year = {2021},
  howpublished = {\url{https://github.com/monk1337/resp}},
  note = {Fetch academic research papers from multiple sources}
}

Support

If you'd like to support this project:

Resp

Install / Use

README