aniwa 0.1.1

Universal dataset profiling and intelligence tool

Aniwa

See your data clearly.

Aniwa is an open-source universal dataset profiling and intelligence tool designed for developers, analysts, data engineers, researchers, and modern data teams.

Aniwa helps you instantly understand datasets through:

• schema profiling
• data quality analysis
• statistical summaries
• intelligent insights
• rich terminal reports
• shareable HTML reports

Whether you're working with CSV files, Excel spreadsheets, JSON datasets, or Parquet files, Aniwa gives you a fast and elegant way to inspect and understand data.

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Why Aniwa?

Data professionals constantly work with unknown datasets.

Before trusting a dataset, people need to know:

• What columns exist?
• What data types are present?
• Are there missing values?
• Are there duplicates?
• Are there suspicious patterns?
• Which columns might contain IDs or PII?
• Is the dataset healthy?

Aniwa makes answering those questions simple.

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Quick Installation

Install Aniwa from PyPI:

pip install aniwa

Verify installation:

aniwa --help

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Quick Start

Profile a dataset:

aniwa customers.csv

Generate a JSON report:

aniwa customers.csv --report json --output profile.json

Generate an HTML report:

aniwa customers.csv --report html --output profile.html

Run lightweight profiling:

aniwa customers.csv --mode fast

Run full profiling:

aniwa customers.csv --mode deep

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Supported Formats

Aniwa currently supports:

• CSV
• Excel (.xlsx)
• JSON
• Parquet

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Features

Universal Dataset Support

Aniwa supports multiple modern dataset formats:

• CSV
• Excel
• JSON
• Parquet

Future releases will include:

• PostgreSQL
• MySQL
• DuckDB
• BigQuery
• Snowflake

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Core Profiling

Aniwa provides:

Dataset Summary

• row counts
• column counts
• dataset size analysis

Schema Profiling

• type inference
• mixed type detection
• schema overview

Data Quality Analysis

• null analysis
• duplicate detection
• uniqueness analysis
• sparse column detection

Statistical Profiling

• minimum values
• maximum values
• mean
• median
• standard deviation

Intelligent Insights

• possible ID detection
• high-cardinality warnings
• sparse column warnings
• suspicious quality patterns

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Reporting

Rich Terminal Reports

Aniwa uses Rich-powered terminal interfaces for beautiful developer-friendly output.

JSON Export

Machine-readable profiling results.

HTML Reports

Generate shareable profiling reports for teams, audits, and debugging workflows.

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Installation

Clone the Repository

git clone https://github.com/ReginaldErzoah/Aniwa.git
cd Aniwa

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Create a Virtual Environment

python -m venv .venv

Activate the environment:

Windows

source .venv/Scripts/activate

macOS/Linux

source .venv/bin/activate

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Install Dependencies

pip install -r requirements.txt

Install Aniwa locally:

pip install -e .

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Usage

Basic Profiling

aniwa examples/customers.csv

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Generate JSON Report

aniwa examples/customers.csv --report json --output profile.json

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Generate HTML Report

aniwa examples/customers.csv --report html --output profile.html

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Fast Profiling Mode

aniwa examples/customers.csv --mode fast

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Deep Profiling Mode

aniwa examples/customers.csv --mode deep

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Example Console Output

┌──────────────────────────────┐
│      Aniwa Dataset Profile   │
├──────────────────────────────┤
│ Rows: 5                      │
│ Columns: 5                   │
│ Duplicate Rows: 1            │
└──────────────────────────────┘

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Project Structure

Aniwa/
│
├── aniwa/
│   ├── cli.py
│   ├── core/
│   ├── io/
│   ├── models/
│   ├── reports/
│   └── utils/
│
├── tests/
├── examples/
├── README.md
├── CONTRIBUTING.md
├── requirements.txt
└── pyproject.toml

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Roadmap

v0.1.1 - MVP Foundation

Core Features

[x] CSV support [x] Excel support [x] JSON support [x] Parquet support [x] schema profiling [x] null analysis [x] duplicate detection [x] statistical profiling [x] console reports [x] JSON export [x] HTML reports

Developer Experience

[x] Rich terminal UI [x] fast and deep modes [x] profiling insights

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v0.2.0 - Intelligence Release

• correlation analysis
• outlier detection
• semantic detection
• improved insights
• Markdown reports

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v0.3.0 - Universal Connectivity

• PostgreSQL support
• MySQL support
• DuckDB support
• BigQuery support
• profiling history
• snapshot management

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v0.4.0 - Extensibility

• plugin system
• custom profiling modules
• community extensions

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v0.5.0 - AI Intelligence

• dataset summarization
• semantic understanding
• AI-powered recommendations
• anomaly explanations

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Philosophy

Aniwa is built around a few core principles:

• universal
• developer-first
• fast
• modular
• intelligent
• beautiful
• automation-friendly

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Contributing

Contributions are welcome.

See CONTRIBUTING.md for:

• development setup
• contribution guidelines
• pull request workflow
• testing instructions

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License

Aniwa is released under the MIT License.

See LICENSE for details.