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 Docker Push workflow status Coverage 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.

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-1.0.0.tar.gz (270.2 kB view details)

Uploaded Source

Built Distribution

flama-1.0.0-py3-none-any.whl (302.6 kB view details)

Uploaded Python 3

File details

Details for the file flama-1.0.0.tar.gz.

File metadata

  • Download URL: flama-1.0.0.tar.gz
  • Upload date:
  • Size: 270.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.10.6 Linux/5.15.0-1031-azure

File hashes

Hashes for flama-1.0.0.tar.gz
Algorithm Hash digest
SHA256 544426193194644ccf46a822a4e80121ffeb7150eda86ba41ded4ddc47818d4f
MD5 5d3b6eda53dbcbe2030de56768161b68
BLAKE2b-256 266511f4ee3d7d0201266f65e339606fac8e5766b13bca9846fbd0384ff57928

See more details on using hashes here.

File details

Details for the file flama-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: flama-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 302.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.10.6 Linux/5.15.0-1031-azure

File hashes

Hashes for flama-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 52b8aa574b5a3b6a4cf5a18613409a9cfda0db2df74443f4dda2bad65d31490f
MD5 6c7d4d18a0c8657310342fdcdb084002
BLAKE2b-256 8f099637ab809a96cf898b83afaa17a4c08ac9d24cfb03d8ce18b8ceffb51347

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