newspaper vs Scrapy

Side-by-side — pricing, strengths, tradeoffs, and fit.

newspaper

Extract news articles and content with Python.

Scrapy

A fast high-level screen scraping and web crawling framework.

At a glance

Open SourceFree Tier
● Established·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

Extract news articles and content with Python.

One-liner

A fast high-level screen scraping and web crawling framework.

Maturity

Established

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Developers who need to extract structured data from news articles in Python projects.
Data scientists working on natural language processing tasks that require clean, curated text data.
Researchers analyzing content trends across different news sources.

✓ Best for

Developers needing a robust framework for large-scale web scraping projects
Data scientists looking to automate data collection from multiple websites
Teams requiring efficient and scalable solutions for crawling complex sites

Not ideal for

✕ Not for

Projects requiring real-time streaming of news updates (newspaper is batch-oriented).
Applications needing extensive customization beyond its core functionalities.

✕ Not for

Projects that require real-time streaming of scraped data (Scrapy is batch-oriented)
Users who prefer a GUI-based tool over command-line interfaces

Strengths

↑ Strengths

Extracts text, metadata, authors, images from news articles.
Supports multiple languages and can detect language automatically.
Can be used for content curation and analysis.
Does not require internet access once data is downloaded.

↑ Strengths

High-performance crawling and scraping capabilities
Built-in support for handling cookies, sessions, and user agents
Flexible item pipeline for processing scraped data
Supports AJAX content via Splash integration

Weaknesses

↓ Weaknesses

Steep learning curve for non-Python developers
Frequent breaking changes between versions
Limited support for non-English languages
Performance issues with large-scale data processing

↓ Weaknesses

Frequent breaking changes between versions
Limited out-of-the-box support for complex scraping scenarios
Performance bottlenecks with very large datasets
Full newspaper profile →Full Scrapy profile →