scimesh

scimesh

A Python library for systematic literature search across multiple academic databases.

Search arXiv, OpenAlex, Scopus, and Semantic Scholar with a unified API. Export to BibTeX, RIS, CSV, JSON, or Workspace. Download PDFs via Open Access (Unpaywall). Index and search full-text content locally.

Features

• Multi-provider search - arXiv, OpenAlex, Scopus, Semantic Scholar (parallel queries)
• Scopus-style query syntax - TITLE(transformers) AND AUTHOR(Vaswani)
• Programmatic query API - Compose queries with Python operators (&, |, ~)
• Export formats - BibTeX, RIS, CSV, JSON, Workspace
• PDF download - Open Access via Unpaywall (Sci-Hub opt-in) with local caching
• Fetch specific papers - Get paper metadata by DOI with scimesh get
• Citation graph - Get papers citing or cited by a paper with scimesh citations
• Fulltext search - Index PDFs locally and search their content with SQLite FTS5
• Metadata merging - Combine paper data from multiple sources for richer results
• Async streaming - Results arrive as they're found
• Automatic deduplication - By DOI or title+year across providers

Installation

Run directly without installing:

uvx scimesh search "TITLE(transformer)"

Install as a CLI tool (recommended):

uv tool install scimesh

Add to a project:

uv add scimesh

With pip:

pip install scimesh

Quick Start

CLI

# Search arXiv and OpenAlex (default providers)
scimesh search "TITLE(transformer) AND AUTHOR(Vaswani)"

# Search multiple providers (comma-separated)
scimesh search "TITLE(BERT)" -p arxiv,openalex,semantic_scholar

# Export to BibTeX
scimesh search "TITLE(BERT)" -f bibtex -o papers.bib

# Download PDFs from search results
scimesh search "TITLE(attention)" -f json | scimesh download -o ./pdfs

# Get a specific paper by DOI
scimesh get "10.1038/nature14539"

# Get papers citing a specific paper
scimesh citations "10.1038/nature14539" --direction in

# Index PDFs for fulltext search
scimesh index ./papers/

# Full text search (uses native API for arXiv/Scopus, local index for others)
scimesh search "ALL(attention mechanism)"

Python API

import asyncio
from scimesh import search, title, author, year, citations
from scimesh.providers import Arxiv, OpenAlex

async def main():
    query = title("transformer") & author("Vaswani") & year(2017, 2023) & citations(50)

    result = await search(
        query,
        providers=[Arxiv(), OpenAlex()],
        max_results=100,
    )

    for paper in result.papers:
        print(f"{paper.title} ({paper.year}) - {paper.citations_count} citations")

asyncio.run(main())

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Query Syntax

Scopus-Style Strings

The library parses Scopus-compatible query strings automatically.

Plain Text Search:

You can search without field specifiers - plain text searches in both title and abstract:

scimesh search "transformers"                    # Same as TITLE-ABS(transformers)
scimesh search "attention mechanism"             # Searches title OR abstract
scimesh search "deep learning AND PUBYEAR > 2020"  # Can combine with operators

Field Operators:

Operator	Description	Example
TITLE(...)	Search in title	TITLE(transformer)
ABS(...)	Search in abstract	ABS(attention mechanism)
KEY(...)	Search in keywords	KEY(machine learning)
TITLE-ABS(...)	Title OR abstract	TITLE-ABS(neural network)
TITLE-ABS-KEY(...)	Title OR abstract OR keywords	TITLE-ABS-KEY(deep learning)
AUTHOR(...)	Search by author	AUTHOR(Vaswani)
AUTH(...)	Alias for AUTHOR	AUTH(Hinton)
DOI(...)	Search by DOI	DOI(10.1038/nature14539)
ALL(...)	Full text search	ALL(protein folding)

Year Operators:

Operator	Description	Example
PUBYEAR = 2023	Exact year	Papers from 2023
PUBYEAR > 2020	After year	Papers from 2021+
PUBYEAR < 2020	Before year	Papers until 2019
PUBYEAR >= 2020	From year	Papers from 2020+
PUBYEAR <= 2023	Until year	Papers until 2023

Citation Operators: