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eLifePathways/sciencebeam-parser

A set of tools to allow PDF to XML conversion, utilising Apache Beam and other tools. The aim of this project is to bring multiple tools together to generate a full XML document.

Python ◇ grobid MIT
★299STARS
⑂32FORKS
!10ISSUES
🏆#6,496GLOBAL RANK
🔥1DAYS TRENDING
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+10

STARS · LAST 30 DAYS

1

PER DAY

#814

MOST-STARRED Python

Window7 days30 days90 days
Stars gained+7+10+90
Per day111
Forks gained+1+3+10

sciencebeam-parser gained 10 stars in the last 30 days, about 1 a day, and now has 299. It is about 9 years old and has averaged roughly 33 stars a year. It ranks #814 among Python repositories and #6,496 across all languages on GitHubRepo.

Trending Record

sciencebeam-parser has maintained a continuous presence across global trending indexes, peaking at #6212. Below is the 30-day activity profile:

💡 Overview

sciencebeam-parser is an open-source project written in Python: A set of tools to allow PDF to XML conversion, utilising Apache Beam and other tools. The aim of this project is to bring multiple tools together to generate a full XML document.

Engineered for speed, consistency, and developer ease, it solves common hurdles in grobid, sciencebeam. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Python for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ pip install sciencebeam-parser

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Python >= 3.9, pip, virtualenv

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

sciencebeam-parser coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Production System Integration

Embed sciencebeam-parser into Python backend services to handle core application logic.

CI/CD Automated Pipelines

Run automated validation, builds, and integration suites during deployments.

Developer Tooling & Workflows

Accelerate developer onboarding with pre-configured project utilities.

Open Source Extension

Fork and customize internal modules under the repository's open MIT license.

🚀 Getting Started

1

Install sciencebeam-parser using your package manager: `pip install sciencebeam-parser`

2

Initialize your project workspace or configuration file for sciencebeam-parser.

3

Import sciencebeam-parser into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `sciencebeam-parser --help` to verify successful setup.

👍 Strengths

Active community backing with 299 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Python for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Python and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

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👥 Who Should Use This

Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

eLifePathways/sciencebeam-parser is currently ranked #6,496 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#6,483 dapr/java-sdk Java ★ 300 Compare ↗
#6,483 kubernetes/org Go ★ 300 Compare ↗
#6,483 auth0/Auth0.Android Kotlin ★ 300 Compare ↗
#6,483 depado/goploader JavaScript ★ 300 Compare ↗
#6,483 Koenvh1/ets2-local-radio JavaScript ★ 300 Compare ↗
#6,496 eLifePathways/sciencebeam-parser This Project Python ★ 299
#6,496 4store/4store C ★ 299 Compare ↗
#6,496 NNTmux/newznab-tmux PHP ★ 299 Compare ↗
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Frequently Asked Questions

What does sciencebeam-parser do? +

A set of tools to allow PDF to XML conversion, utilising Apache Beam and other tools. The aim of this project is to bring multiple tools together to generate a full XML document.

What language is sciencebeam-parser written in? +

The primary language is Python. Topics include: grobid, sciencebeam.

Is sciencebeam-parser actively maintained? +

Yes, the last recorded push was on Oct 1, 2026 with 10 open issues being tracked.

How many stars does sciencebeam-parser have? +

sciencebeam-parser has 299 stars and 32 forks on GitHub.

How does sciencebeam-parser rank among GitHub repositories? +

With 299 stars, eLifePathways/sciencebeam-parser is ranked #6,496 globally across all repositories tracked on GitHubRepo and #814 among Python projects.

What license is sciencebeam-parser distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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