Skip to main content

Fire up your models with the flame 🔥

Project description

Flama

Fire up your models with the flame 🔥

Test And Publish workflow status Package version PyPI - Python Version


Flama

Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code.

The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution for the development of asynchronous and production-ready services, offering automatic deployment for ML models.

Some remarkable characteristics:

  • Generic classes for API resources with the convenience of standard CRUD methods over SQLAlchemy tables.
  • A schema system (based on Marshmallow or Typesystem) which allows the declaration of inputs and outputs of endpoints very easily, with the convenience of reliable and automatic data-type validation.
  • Dependency injection to make ease the process of managing parameters needed in endpoints via the use of Components. Flama ASGI objects like Request, Response, Session and so on are defined as Components ready to be injected in your endpoints.
  • Components as the base of the plugin ecosystem, allowing you to create custom or use those already defined in your endpoints, injected as parameters.
  • Auto generated API schema using OpenAPI standard.
  • Auto generated docs, and provides a Swagger UI and ReDoc endpoints.
  • Automatic handling of pagination, with several methods at your disposal such as limit-offset and page numbering, to name a few.

Installation

Flama is fully compatible with all supported versions of Python. We recommend you to use the latest version available.

For a detailed explanation on how to install flama visit: https://flama.dev/docs/getting-started/installation.

Getting Started

Visit https://flama.dev/docs/getting-started/quickstart to get started with Flama.

Documentation

Visit https://flama.dev/docs/ to view the full documentation.

Example

from flama import Flama

app = Flama(
    title="Hello-🔥",
    version="1.0",
    description="My first API",
)


@app.route("/")
def home():
    """
    tags:
        - Salute
    summary:
        Returns a warming message
    description:
        This is a more detailed description of the method itself.
        Here we can give all the details required and they will appear
        automatically in the auto-generated docs.
    responses:
        200:
            description: Warming hello message!
    """
    return {"message": "Hello 🔥"}

This example will build and run a Hello 🔥 API. To run it:

flama run examples.hello_flama:app

Authors

Contributing

This project is absolutely open to contributions so if you have a nice idea, please read our contributing docs before submitting a pull request.

Star History

Star History Chart

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

flama-1.9.2.tar.gz (299.1 kB view details)

Uploaded Source

Built Distribution

flama-1.9.2-py3-none-any.whl (345.8 kB view details)

Uploaded Python 3

File details

Details for the file flama-1.9.2.tar.gz.

File metadata

  • Download URL: flama-1.9.2.tar.gz
  • Upload date:
  • Size: 299.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.4 CPython/3.10.12 Linux/6.5.0-1025-azure

File hashes

Hashes for flama-1.9.2.tar.gz
Algorithm Hash digest
SHA256 cc59715afe59d51c301cf28d187f64d38aa53e104394dd530534e783a9d6a536
MD5 6a7368b792accb6a52a3ddb17a9565ce
BLAKE2b-256 16488fd9703a0c68b295dfbf63834cf7dc252caaa66ec8f669a406cf5f42c165

See more details on using hashes here.

File details

Details for the file flama-1.9.2-py3-none-any.whl.

File metadata

  • Download URL: flama-1.9.2-py3-none-any.whl
  • Upload date:
  • Size: 345.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.4 CPython/3.10.12 Linux/6.5.0-1025-azure

File hashes

Hashes for flama-1.9.2-py3-none-any.whl
Algorithm Hash digest
SHA256 491d843800628151a79cc40adef418710f5dfe7aa7fa0b00a53e4c90444d97fd
MD5 d6ecb2fd8ec92370e55e7976045853ff
BLAKE2b-256 379dfb04bdb1e2deafae492a825faaec914084727b2b5169b6efb3df4c11e4d4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page