✨ Lila Framework v1.2.8 is Live

Python Web Development

A high-performance async framework built on Starlette and Pydantic. Designed for absolute simplicity, maximum flexibility, and lightning speed.

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Designed for Modern APIs & Web Apps

Lila combines the asynchronous execution power of Starlette and the rapid, bulletproof data validation of Pydantic. It empowers you to build highly scalable RESTful services with automatic routing and built-in database tools.

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Search Engine Integrated

Lila features dynamic automated integrations with SEO metadata tools, optimized for Google Bots and AI scrapers.

* Supports Python 3.9+ with native async/await coroutines.

Recommended: 3.13 version
$ python -m venv venv
$ source venv/bin/activate # Windows: venv\Scripts\activate
$ pip install lila-framework
$ lila-init
$ lila-migrations
$ lila-create-panel-admin
$ python main.py
⚡ System compiled successfully

Engineered for Superior Developer Experience

Lila provides robust tools out of the box to significantly accelerate your development cycles.

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Simplicity First

Intuitive and minimalist design. Lila is built to be simple to write, offering an elegant framework API that gets you running in seconds.

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Flexibility

Supports SQLite, MySQL, and PostgreSQL seamlessly. Easily adapt to any infrastructure model, from simple scripts to production scale.

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Maximum Speed

Powered by Starlette async coroutines, Lila delivers extremely low latency for real-time application handlers and REST interfaces.

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Strict Validation

Utilizes Pydantic parsing systems to guarantee robust, type-checked inputs and outputs. Never let malformed payloads pass your routes.

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Automatic Admin Panel

Generate fully customizable admin dashboard tools instantaneously. Track your system resources, server metrics, and view real-time logs.

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Built-in i18n

Native localization architecture to build systems supporting dynamic content translation tailored to user location and preferences.

Extreme Concurrency Performance

Scientific proof of our Single-Flight query deduplication & route caching. Mitigate RAM and CPU usage under heavy load.

How Lila Avoids DB & CPU Starvation

By default, running multiple concurrent database queries in web applications locks the threads or exhausts connection pools. Lila resolves this via an advanced Single-Flight Query Deduplication (run_async) engine.

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    Single DB Hit: If 10,000 concurrent requests request the same query simultaneously, Lila hits the database only once, collapsing the rest into a shared lightweight Future.

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    Low CPU & RAM Footprint: Under a massive load of 50,000 requests, RAM usage stays around 132 MB, and CPU usage stays below 52%. No thread context switching overhead.

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    Zero Timeout Errors: Bypasses typical connection pool starvation problems of traditional Python web frameworks.

Concurrency Benchmark 127.0.0.1:8000

# 1,000 concurrent requests

✅ Finished in 1.0688 seconds

# 10,000 concurrent requests

✅ Finished in 10.0518 seconds

# 50,000 concurrent requests

✅ Finished in 74.2569 seconds

RAM: ~132MB (Max) CPU: ~52% (Max)