Metadata-Version: 2.4
Name: bizx
Version: 0.1.0
Summary: A unified Python ecosystem for Data Engineering, AI, ML, GenAI, MLOps, and cloud-native analytics.
Author: Saman Siadati
License-Expression: MIT
Project-URL: Homepage, https://github.com/samansiadati/bizx
Project-URL: Repository, https://github.com/samansiadati/bizx
Project-URL: Issues, https://github.com/samansiadati/bizx/issues
Keywords: data,data-engineering,ai,artificial-intelligence,machine-learning,generative-ai,genai,llm,mlops,cloud,aws,spark,databricks
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
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Dynamic: license-file

# BizX

### The Python ecosystem for Data Engineering, Artificial Intelligence, Generative AI, MLOps, and Cloud-Native Analytics.

[![PyPI](https://img.shields.io/pypi/v/bizx.svg)](https://pypi.org/project/bizx/)
[![Python](https://img.shields.io/pypi/pyversions/bizx.svg)](https://pypi.org/project/bizx/)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
[![GitHub Stars](https://img.shields.io/github/stars/samansiadati/bizx.svg)](https://github.com/samansiadati/bizx/stargazers)
[![GitHub Issues](https://img.shields.io/github/issues/samansiadati/bizx.svg)](https://github.com/samansiadati/bizx/issues)

---

## 🚀 What is BizX?

**BizX** is an open-source Python ecosystem designed to provide a unified foundation for modern **Data, AI, and Cloud Engineering**.

The project brings commonly used capabilities across data engineering, machine learning, generative AI, MLOps, evaluation, observability, and cloud platforms into a consistent and modular Python ecosystem.

The vision is simple:

> **Build a unified, composable, production-oriented ecosystem for Data and AI engineering with Python.**

BizX is designed to grow from a lightweight Python foundation into a broader ecosystem of reusable components for developers, data engineers, AI engineers, researchers, and organizations.

---

## 🌐 The BizX Ecosystem

```text
                                ┌─────────────────────┐
                                │        BIZX         │
                                │  Data & AI Platform │
                                └──────────┬──────────┘
                                           │
             ┌─────────────────────────────┼─────────────────────────────┐
             │                             │                             │
             ▼                             ▼                             ▼
      ┌──────────────┐             ┌──────────────┐             ┌──────────────┐
      │     DATA     │             │      AI      │             │    CLOUD     │
      └──────┬───────┘             └──────┬───────┘             └──────┬───────┘
             │                            │                            │
       ┌─────┼─────┐              ┌──────┼──────┐              ┌──────┼──────┐
       │     │     │              │      │      │              │      │      │
      SQL   ETL   Spark           ML     LLM    RAG            AWS   Azure  Databricks
       │     │     │              │      │      │              │
       └─────┼─────┘              │   Agents    │           Bedrock
             │                    │   Eval      │           Glue
             │                    │             │           S3
             │                    └──────┬──────┘
             │                           │
             └───────────────────────────┼──────────────────────────────┐
                                         ▼                              │
                                  ┌──────────────┐                       │
                                  │    MLOps     │                       │
                                  └──────┬───────┘                       │
                                         │                              │
                              ┌──────────┼──────────┐                   │
                              │          │          │                   │
                            Train     Deploy     Monitor                │
                              │          │          │                   │
                              └──────────┼──────────┘                   │
                                         ▼                              │
                                Evaluation & Observability ◄───────────┘
```

---

# ✨ Key Areas

BizX is organized into modular domains.

### 📊 Data Engineering

Tools for building reliable data pipelines and working with structured and unstructured data.

Planned capabilities include:

* DataFrames
* Data validation
* Data profiling
* Data quality
* ETL / ELT
* SQL utilities
* Data transformation
* Data serialization
* Distributed data processing
* Apache Spark / PySpark integrations

```python
from bizx.data import DataProfiler

profile = DataProfiler(df)
report = profile.generate()
```

---

### 🤖 Artificial Intelligence & Machine Learning

Reusable components for traditional machine learning and AI workflows.

Planned capabilities include:

* Model utilities
* Training pipelines
* Feature engineering
* Model evaluation
* Experiment management
* Prediction utilities
* AI pipelines

```python
from bizx.ai import ModelEvaluator

result = ModelEvaluator.evaluate(
    model=model,
    dataset=test_data
)
```

---

### 🧠 Generative AI & LLMs

BizX will provide a unified foundation for modern generative AI applications.

Planned capabilities include:

* LLM clients
* Prompt management
* Embeddings
* Vector search
* RAG
* AI agents
* LLM evaluation
* Hallucination detection
* Context management
* AI safety and governance

```python
from bizx.llm import LLMClient

llm = LLMClient(...)
response = llm.generate(
    "Explain the architecture of a modern data platform."
)
```

---

### ⚙️ MLOps & AI Operations

Production-oriented tooling for deploying, evaluating, monitoring, and maintaining AI systems.

Planned capabilities include:

* Experiment tracking
* Model monitoring
* Data drift detection
* Model drift detection
* LLM evaluation
* AI observability
* Pipeline monitoring
* Performance monitoring
* Production diagnostics

---

### ☁️ Cloud Integrations

BizX is designed to integrate with major cloud and data platforms without making the core framework dependent on a specific provider.

Planned integrations include:

#### AWS

* Amazon Bedrock
* Amazon S3
* AWS Glue
* Amazon OpenSearch
* Amazon SageMaker
* AWS Lambda
* API Gateway

#### Databricks

* Databricks
* Delta Lake
* MLflow
* Spark

#### Other platforms

Additional cloud and data-platform integrations may be added as the ecosystem develops.

---

# 🏗️ Architecture

BizX follows a modular architecture.

```text
bizx/
│
├── core/          # Foundational abstractions
│
├── data/          # Data engineering
│
├── ai/            # AI / ML
│
├── llm/           # Generative AI / LLMs
│
├── mlops/         # MLOps / AI operations
│
├── aws/           # AWS integrations
│
├── spark/         # Apache Spark integrations
│
└── utils/         # General-purpose utilities
```

The architectural principle is:

```text
                    bizx.core
                        │
        ┌───────────────┼────────────────┐
        │               │                │
       data             ai              llm
        │               │                │
        └───────────────┼────────────────┘
                        │
                      mlops
                        │
                  Cloud Platforms
```

The `core` layer should remain lightweight and stable.

Domain-specific modules should build on the core rather than introducing unnecessary coupling between unrelated parts of the ecosystem.

---

# 🎯 Design Principles

BizX is built around several principles.

## Simple

Common Data and AI tasks should require minimal code.

## Modular

Users should be able to install and use only the functionality they need.

```bash
pip install bizx
```

or:

```bash
pip install "bizx[data]"
```

```bash
pip install "bizx[ai]"
```

```bash
pip install "bizx[llm]"
```

```bash
pip install "bizx[aws]"
```

```bash
pip install "bizx[spark]"
```

---

## Composable

Individual components should be usable independently and combined into larger workflows.

```text
Data → Transform → Validate → Model → Evaluate → Deploy → Monitor
```

---

## Production-Oriented

BizX is intended to support real-world systems rather than only experimental notebooks.

Important concerns include:

* Testing
* Logging
* Configuration
* Observability
* Reproducibility
* Error handling
* Evaluation
* Security

---

## Cloud-Agnostic Core

The core BizX framework should not depend on a particular cloud provider.

Cloud-specific functionality belongs in dedicated integration modules.

```text
bizx.core
    │
    ├── bizx.aws
    ├── bizx.databricks
    └── future integrations
```

---

## Open Source

BizX is designed to be developed openly and collaboratively.

Contributions, discussions, ideas, bug reports, and improvements are welcome.

---

# 📦 Installation

## Basic Installation

```bash
pip install bizx
```

## Data

```bash
pip install "bizx[data]"
```

## AI / Machine Learning

```bash
pip install "bizx[ai]"
```

## Generative AI / LLM

```bash
pip install "bizx[llm]"
```

## AWS

```bash
pip install "bizx[aws]"
```

## Apache Spark

```bash
pip install "bizx[spark]"
```

## Complete Ecosystem

```bash
pip install "bizx[all]"
```

---

# ⚡ Quick Start

```python
import bizx

print(bizx.__version__)
```

Example data workflow:

```python
from bizx.data import DataProfiler

profiler = DataProfiler(df)

report = profiler.generate()

print(report)
```

Example AI evaluation:

```python
from bizx.ai import ModelEvaluator

result = ModelEvaluator.evaluate(
    model=model,
    dataset=test_dataset
)

print(result)
```

Example LLM workflow:

```python
from bizx.llm import LLMClient

llm = LLMClient(...)

response = llm.generate(
    "What is retrieval-augmented generation?"
)

print(response)
```

> **Note:** APIs shown above represent the planned public interface and may change during the pre-1.0 development period.

---

# 🗺️ Roadmap

BizX is being developed incrementally.

## Phase 1 — Foundation

* [ ] Core package architecture
* [ ] Configuration
* [ ] Common exceptions
* [ ] Logging
* [ ] Common types
* [ ] Testing framework
* [ ] CI/CD
* [ ] Documentation system
* [ ] PyPI packaging

## Phase 2 — Data

* [ ] Data utilities
* [ ] Data validation
* [ ] Data profiling
* [ ] Data quality
* [ ] Data transformation
* [ ] SQL utilities
* [ ] ETL/ELT utilities

## Phase 3 — AI / ML

* [ ] ML utilities
* [ ] Model interfaces
* [ ] Evaluation
* [ ] Feature utilities
* [ ] AI pipelines

## Phase 4 — Generative AI

* [ ] LLM interfaces
* [ ] Prompt utilities
* [ ] Embeddings
* [ ] RAG
* [ ] Vector search
* [ ] Agent utilities
* [ ] LLM evaluation

## Phase 5 — MLOps

* [ ] Experiment tracking
* [ ] Model monitoring
* [ ] Data drift
* [ ] Model drift
* [ ] AI observability
* [ ] Production evaluation

## Phase 6 — Cloud

* [ ] AWS
* [ ] Amazon Bedrock
* [ ] Amazon S3
* [ ] AWS Glue
* [ ] Amazon SageMaker
* [ ] Amazon OpenSearch
* [ ] Databricks
* [ ] Apache Spark

## Phase 7 — BizX 1.0

The `1.0.0` release will establish the first stable public API.

The objective is to provide a reliable foundation for building production-oriented Data and AI applications with BizX.


---


# 🧪 Development

Clone the repository:

```bash
git clone https://github.com/samansiadati/bizx.git
cd bizx
```

Create a virtual environment:

```bash
python -m venv .venv
```

Activate it:

### Linux / macOS

```bash
source .venv/bin/activate
```

### Windows

```powershell
.venv\Scripts\activate
```

Install the development dependencies:

```bash
pip install -e ".[dev]"
```

Run tests:

```bash
pytest
```

---

# 🤝 Contributing

Contributions are welcome.

Before submitting a pull request:

1. Create a feature branch.
2. Add or update tests.
3. Update documentation where appropriate.
4. Ensure the test suite passes.
5. Submit a pull request describing the change.

See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed contribution guidelines.

---

# 🔐 Security

Security issues should not be reported through public GitHub issues.

Please see [SECURITY.md](SECURITY.md) for information about responsible disclosure.

---

# 📚 Documentation

Documentation will be developed alongside the project.

Planned documentation areas include:

* Getting Started
* Core API
* Data Engineering
* AI / ML
* Generative AI
* LLMs
* MLOps
* Cloud Integrations
* Examples
* Architecture
* Developer Guide

---

# 📈 Project Status

**Current status: Alpha / Early Development**

BizX is under active development.

The API is expected to evolve before the `1.0.0` release.

Early users and contributors are encouraged to provide feedback on architecture, APIs, documentation, and functionality.

---

# 🧭 Long-Term Vision

The long-term goal of BizX is to provide a coherent Python ecosystem covering the complete lifecycle of modern Data and AI systems:

```text
                 DATA
                   │
                   ▼
              Preparation
                   │
                   ▼
              Engineering
                   │
                   ▼
              AI / ML / LLM
                   │
                   ▼
              Evaluation
                   │
                   ▼
                 MLOps
                   │
                   ▼
               Deployment
                   │
                   ▼
              Observability
                   │
                   ▼
             Production AI
```

Rather than creating isolated utilities, BizX aims to provide reusable building blocks that can be composed into complete production systems.

---

# 👨‍💻 Author

**Saman Siadati**

BizX is an open-source project focused on building practical infrastructure and tools for modern Data and AI engineering.

---

# 📄 License

BizX is released under the **MIT License**.

See [LICENSE](LICENSE) for the complete license text.

---

## ⭐ Support the Project

If you find BizX useful:

* ⭐ Star the repository
* 🐛 Report bugs
* 💡 Suggest improvements
* 📖 Improve documentation
* 🔧 Submit pull requests
* 📢 Share the project

---

**BizX — One ecosystem for Data, AI, and Cloud Engineering.**
