# leovan/SciHubEVA

A Cross Platform Sci-Hub GUI Application

Repository: https://github.com/leovan/SciHubEVA
Canonical: https://ross.abutalabs.com/products/scihubeva
Language: Python
License: MIT
License Family: permissive
Topics: qt, qtquick, qml, pyside6, scihub, python
Last push: 2026-03-08T03:00:49+00:00

## Health v2 (maintenance only)
Score: 74/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 71, release rhythm 62, longevity 100
- inputs: {"age_days": 3028, "days_push": 178, "days_rel": 178, "gap_med": 62.0, "n_releases_24m": 5}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1107, forks 161 (observed 2026-08-28T04:03:36.692794+00:00)

## What it is
SciHubEVA is a cross-platform GUI application for searching and downloading papers from Sci-Hub, built with Python and Qt (PySide6/QML). It supports queries by URL, PMID, DOI, or title, including range and batch file queries.

## Use cases
- download academic papers by DOI
- batch download papers from a list of DOIs
- search sci-hub by paper title
- download a range of PMIDs
- export failed queries from download logs

## When to choose
- you want a GUI instead of scripts for fetching papers from Sci-Hub
- you need batch or range-based paper downloads
- you need a cross-platform desktop tool with proxy and captcha support

## When to avoid
- you need legally sourced open-access papers only (use Unpaywall or publisher APIs)
- your IP is blocked by DDoS-Guard and you cannot run FlareSolverr or a proxy
- you need a headless/CLI solution for server automation

## Facets
- artifact type: application
- maturity: active
- function: gui, web-scraping, pdf, developer-tools
- domain: education, pdf, cross-platform, developer-tools
- platform: cross-platform, python, windows
- tags: scihub, pyside6, qt, qml, academic-papers, paper-downloader, doi, desktop, macos, linux

## Member repositories
- leovan/SciHubEVA (main) score 74

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:36.692794+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:44:02.361586+00:00, confidence not recorded.
  - readme: https://github.com/leovan/SciHubEVA (fetched 2026-08-28T04:03:36.692794+00:00, sha d2b9da296a07)
- Data as of 2026-08-30T08:39:29.467469+00:00.