Artifician
Github Repository
  • Introduction
    • “Turn your data preparation nightmares into a dream.”
    • Why Artifician?
    • Simple Example
    • Without Artifician
    • Using Artifician
    • Output
  • Getting Started with Artifician
    • Pre-requisites
    • Installation
    • Using pip
    • Using conda
    • Verify Installation
    • Next Steps
  • Quick Start
    • Define Extractor
    • Initialize components
    • Subscriptions
    • Dataset Preparation
    • Output
  • Advanced Concepts
    • Processor Chaining
      • Overview
      • Key Features
      • Syntax Showcase
      • Example Scenario: NLP Processing Pipeline
      • Building an NLP Pipeline with processor chaining
      • Output
    • Defining Custom Extractors
      • Introduction
      • Why Custom Extractors?
      • How Extractors Work
      • Example of a Simple Extractor
      • Integrating Custom Extractors
      • Advanced Usage
      • Conclusion
    • Defining Custom Processors
      • Introduction
      • Why Custom Processors?
      • How Processors Work
      • Example of a Simple Processor
      • Integrating Custom Processors
      • Advanced Usage
      • Conclusion
    • Library Architecture
      • Events
      • Dataset
      • Feature Definition
      • Processors
      • Extractors
  • API Reference
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  • Processor Chaining
  • Defining Custom Extractors
  • Defining Custom Processors
  • Library Architecture

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Advanced Concepts

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Last updated 1 year ago

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The Artifician library is designed to be easy to use for simple tasks, yet flexible enough for complex data preparation workflows. In this section, we will delve into the more advanced features and architectural choices that power the Artifician library.

Whether you’re looking to extend the library’s capabilities or trying to get a deeper understanding of how things work, these advanced topics will provide you with the knowledge you need.

Defining Custom Processors
Library Architecture
Introduction
Why Custom Processors?
How Processors Work?
Example of a Simple Processor
Integrating Custom Processors
Advanced Usage
Conclusion
Processor Chaining
Defining Custom Extractors
Events
Dataset
Feature Definition
Processors
Extractors
Introduction
Why Custom Extractors?
How Extractors Work?
Example of a Simple Extractor
Integrating Custom Extractors
Advanced Usage
Conclusion
Overview
Key Features
Syntax Showcase
Example Scenario: NLP Processing Pipeline
Building an NLP Pipeline with PCM
Output