DATAMIMIC Community Edition 🌟

🚀 Quick Intro

DATAMIMIC is an AI-powered, model-driven test data generation platform designed to quickly deliver realistic, privacy-compliant synthetic data.

✅ Model-driven | ✅ AI-ready | ✅ Privacy-focused | ✅ Open Source (MIT)

📞 Book your Free Strategy Call and Demo to explore the full power of our Enterprise solution!

🟢 Community vs 🟣 Enterprise Editions

👉 Learn more about Enterprise Edition

📦 Installation

Install easily via pip:

pip install datamimic-ce

Verify installation:

datamimic version

⚡ Quick Start

Generate realistic data effortlessly:

Python Example:

from datamimic_ce.domains.common.services import PersonService

person_service = PersonService(dataset="US")
person = person_service.generate()

print(f"Person: {person.name}, Email: {person.email}")

XML Example:

<setup>
  <generate name="user_data" count="10" target="CSV">
    <key name="name" entity="Person().name"/>
    <key name="email" entity="Person().email"/>
  </generate>
</setup>

Run XML via CLI:

datamimic run datamimic.xml

⚙️ Custom Domain Factory Example

Quickly generate test-specific data using DataMimicTestFactory:

customer.xml:

<setup>
    <generate name="customer" count="10">
        <variable name="person" entity="Person(min_age=21, max_age=67)"/>
        <key name="id" generator="IncrementGenerator"/>
        <key name="first_name" script="person.given_name"/>
        <key name="last_name" script="person.family_name"/>
        <key name="email" script="person.email"/>
        <key name="status" values="'active', 'inactive', 'pending'"/>
    </generate>
</setup>

Python Usage:

from datamimic_ce.factory.datamimic_test_factory import DataMimicTestFactory

customer_factory = DataMimicTestFactory("customer.xml", "customer")
customer = customer_factory.create()

print(customer["id"])  # 1
print(customer["first_name"])  # Jose
print(customer["last_name"])   # Ayers

🎯 Why DATAMIMIC?

• 🚀 Accelerate Development: Instantly create test data.
• 🛡️ Privacy First: Built-in GDPR compliance.
• 📊 Realistic Data: Authentic, weighted distributions from various data domains.
• 🔧 High Flexibility: Easily model, standardize, and customize data generation processes.
• 📥📤 Versatile Sources: Extensive import/export capabilities (JSON, XML, CSV, RDBMS, MongoDB, etc.).
• 🗃️ Metadata-Driven: Operate seamlessly with an integrated metadata model.

🌐 Documentation & Demos

• 📚 Full Documentation
• 🚀 Run an instant demo:

datamimic demo create healthcare-example
datamimic run ./healthcare-example/datamimic.xml

📘 Additional Resources

• CLI Interface
• Data Domains Details

❓ FAQ

Q: Is Community Edition suitable for commercial projects?

A: Absolutely! DATAMIMIC CE uses the MIT License.

Q: Why upgrade to Enterprise Edition (EE) instead of using Community Edition (CE)?

A: EE provides a web UI, enterprise support, team collaboration, and advanced features like AI-powered test data generation, workflow automation, and compliance tools.

Q: Can I contribute?

A: Yes! See Contributing Guide.

🛠️ Support & Community

• 💬 GitHub Discussions
• 🐛 Issue Tracker
• 📧 Email Support

🌟 Stay Connected

• 🌐 Website
• 💼 LinkedIn

⭐ Star us on GitHub to keep DATAMIMIC growing!