Outlier-X API

Welcome to the Outlier-X Repository. This repository contains production-grade Python CLI and tools for Outlier.bet data ingestion, normalization, and validation. The following documentation will guide you through setup, usage, development practices, and deployment workflows.

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Table of Contents

• Overview
• Installation
• Usage
  • Quick Start Guide
  • CLI Commands
• Development
• Testing
• Deployment
• Contributing

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Overview

The Outlier-X project serves as the backbone for data handling at Outlier.bet. It provides tools for seamless data ingestion, robust validation pipelines, and normalization routines to ensure data consistency.

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Installation

1. Clone Repository

   git clone https://github.com/allsxxing/outlier-x.git
   cd outlier-x

2. Create Python Virtual Environment

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies

   pip install -r requirements.txt

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Usage

Quick Start Guide

1. Run the CLI tool:

   python cli.py --help

   Example command:

   python cli.py ingest --source "example.csv"

2. Normalize data:

   python cli.py normalize --input "raw_data.json" --output "normalized_data.json"

3. Validate data:

   python cli.py validate --schema "schema.json" --data "normalized_data.json"

CLI Commands

Command	Arguments	Description
ingest	--source FILE	Data ingestion from a source file.
normalize	--input FILE --output FILE	Normalize raw data to consistent format.
validate	--schema FILE --data FILE	Validate data against the given schema.

(Expand the commands table for additional features.)

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Development

1. Linting Run the linter to enforce code quality:

   ruff src tests

2. Code Formatting Apply consistent formatting:

   black src tests

3. Run Tests Execute all automated tests:

   pytest

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Testing

Tests are written using the pytest framework. Run individual test files or the entire test suite as needed. Use structured data examples to build test coverage for edge cases.

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Deployment

Deployment for Outlier-X tools can occur on any Python-compatible server. Optionally, containerize it using Docker for simplified scaling and portability.

1. Build Docker Image

   docker build -t outlier-x:latest .

2. Run Docker Container

   docker run --rm -it outlier-x:latest

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Contributing

1. Fork the repository and create feature or bugfix branches.
2. Ensure all changes pass linting and tests before creating a pull request.
3. Reference issues in commits and PRs wherever applicable.

Thank you for contributing to Outlier-X!