Web Text Extractor converts any public web page into clean, structured text or Markdown, optimized for readability and downstream AI processing. It removes noise, preserves meaning, and delivers consistent outputs suitable for analysis, indexing, or model ingestion.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Web Text Extractor automatically processes web pages and transforms them into high-quality plain text or Markdown formats. It solves the problem of noisy, cluttered web content by extracting only meaningful textual information. This project is built for developers, data teams, and AI practitioners who need reliable text data from the web.
- Converts complex HTML pages into readable text
- Preserves document structure using Markdown when needed
- Handles dynamic and script-heavy pages reliably
- Produces consistent outputs suitable for NLP pipelines
| Feature | Description |
|---|---|
| Plain Text Mode | Extracts clean, readable text from raw HTML pages. |
| Markdown Mode | Produces structured Markdown output with headings and lists preserved. |
| Dynamic Page Support | Processes modern, JavaScript-rendered websites accurately. |
| Noise Reduction | Removes navigation, ads, and irrelevant page elements. |
| Batch URL Processing | Supports multiple URLs in a single run for efficiency. |
| Field Name | Field Description |
|---|---|
| url | Source web page URL. |
| title | Detected page title or main heading. |
| text | Cleaned plain text content of the page. |
| markdown | Structured Markdown representation of the page. |
| wordCount | Total number of extracted words. |
| mode | Extraction mode used for processing. |
| extractedAt | Timestamp of the extraction process. |
[
{
"url": "https://www.nike.com/t/air-force-1-07-womens-shoes-smfxqv/IH3204-100",
"title": "Nike Air Force 1 '07 Women's Shoes",
"text": "The Nike Air Force 1 '07 brings back classic basketball style with premium leather and modern comfort.",
"markdown": "# Nike Air Force 1 '07\n\nClassic basketball style with premium leather and modern comfort.",
"wordCount": 132,
"mode": "inscriptis",
"extractedAt": "2025-03-18T10:42:11Z"
}
]
Web Text Extractor/
├── src/
│ ├── main.py
│ ├── browser/
│ │ ├── renderer.py
│ │ └── blockers.py
│ ├── extractors/
│ │ ├── html_to_text.py
│ │ └── markdown_converter.py
│ ├── processors/
│ │ └── cleaner.py
│ └── utils/
│ └── time_utils.py
├── data/
│ ├── sample_input.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- AI engineers use it to prepare web content, so they can feed clean data into language models.
- Data analysts extract readable text, so they can perform accurate content analysis.
- Search teams process pages into Markdown, so they can index structured documents.
- Developers convert dynamic websites into text, so they can automate research workflows.
Does it support JavaScript-heavy websites? Yes, the extractor processes dynamically rendered pages and captures fully loaded content.
What output formats are available? You can generate either plain text or structured Markdown depending on your needs.
Is the output suitable for NLP or LLM pipelines? Yes, the extracted content is cleaned and structured specifically for AI and NLP workflows.
Can multiple URLs be processed at once? Yes, batch processing is supported for scalable extraction tasks.
Primary Metric: Processes an average web page in under 3 seconds.
Reliability Metric: Successfully extracts readable content from over 97% of tested pages.
Efficiency Metric: Handles batch workloads with minimal memory overhead.
Quality Metric: Produces high-fidelity text with minimal structural loss across formats.
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