Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

crosslinker

Package Overview
Dependencies
Maintainers
1
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

crosslinker

CrossLinker: A Python Library for SEO - Friendly HTML Text Processing and Keyword Linking

  • 0.0.3
  • PyPI
  • Socket score

Maintainers
1

.. _crosslinker-documentation:

CrossLinker Documentation

Description

CrossLinker is a Python library designed for intelligently linking specific keywords within HTML text content. It enhances SEO (Search Engine Optimization) strategies by optimizing content with linked keywords, maintaining readability, and preventing over-optimization.

Table of Contents

  1. Installation <#installation>_
  2. How It Works <#how-it-works>_
    • Initialization <#initialization>_
    • Text Processing <#text-processing>_
    • Randomization (Optional) <#randomization-optional>_
    • Benefits for SEO <#benefits-for-seo>_
  3. Usage <#usage>_
    • Example <#example>_
    • Parameters <#parameters>_
    • Result <#result>_

Installation

To install CrossLinker, you can use pip:

.. code-block:: bash

pip install crosslinker

Text Processing

The library processes the HTML text and replaces keywords with links. This process includes tokenization, keyword matching, link insertion, HTML escaping, punctuation handling, and link limitation.

Randomization (Optional)

You can choose to place links randomly (if random_links is set to True), which can help avoid over-optimization penalties from search engines.

Initialization

To get started, create an instance of the CrossLinker class by providing the following parameters:

  • html_text: The HTML text content you want to process. (Required)
  • keywords: A list of keyword-link pairs where each item is a list with the keyword and its associated link. (Required)
  • density: The maximum allowed length (in characters) for linked text snippets. (Default: 500)
  • random_links: If set to True, the library will randomly choose keywords to link each time. If False, it will consistently link the same keywords. (Default: False)
  • stemming: If set to True, keywords are stemmed before processing. (Default: True)
  • language: The language to use for stemming. Supported languages include "arabic," "danish," "dutch," "english," "finnish," "french," "german," "hungarian," "italian," "norwegian," "porter," "portuguese," "romanian," "russian," "spanish," and "swedish." (Default: "english")
  • valid_tags: A list of HTML tags that are considered valid for keyword linking. (Default: ["p", "h1", "h2", "h3", "h4", "h5", "h6"])

Benefits for SEO

CrossLinker offers several benefits for SEO:

  • Keyword Linking: It automatically identifies and links keywords to relevant URLs within your HTML content, improving search engine understanding and rankings.
  • Content Optimization: By strategically linking keywords, you can enhance the SEO value of your content and increase its visibility in search results.
  • Prevents Over-Optimization: The library limits the number of linked keywords to maintain a natural keyword density, helping you avoid SEO penalties.
  • Maintains Readability: Linked keywords are embedded within readable text snippets, improving the user experience and preventing content from appearing spammy.

Usage

Here's an example of how to use the CrossLinker library:

Example

.. code-block:: python

from crosslinker import CrossLinker

html_text = """
<h1>Enhance Your SEO with CrossLinker</h1>
<p>CrossLinker is a powerful Python library that can help boost your website's SEO performance. By intelligently linking specific keywords within your content, you can improve search engine rankings and increase organic traffic.</p>
<p>Here are some examples of keywords you can link:</p>
<ul>
    <li>Search Engine Optimization</li>
    <li>Keyword Research</li>
    <li>On-Page SEO</li>
    <li>Link Building</li>
</ul>
"""

keywords = [
    [["Search Engine Optimization"], "https://example.com/seo"],
    [["Keyword Research"], "https://example.com/keyword-research"],
    [["On-Page SEO"], "https://example.com/on-page-seo"],
    [["Link Building"], "https://example.com/link-building"],
    # Add more keyword-link pairs as needed
]

# Initialize CrossLinker
seo_html = CrossLinker(
    html_text=html_text,
    keywords=keywords,
    density=100,
    random_links=False,
    stemming=True,
    language="english",
    valid_tags=["li", "p", "h1", "h2", "h3", "h4", "h5", "h6"],
)

# Generate the processed HTML content
processed_html = seo_html.make()

print(processed_html)

Result

The processed_html variable will contain the HTML content with keywords replaced by links. This processed content can be used to enhance SEO strategies.

Thank you!

Please feel free to reach out if you have any further questions or need additional assistance!

FAQs


Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc