Skip to main content

fal is an easy-to-use Serverless Python Framework

Project description

PyPI Tests

fal

fal is a serverless Python runtime that lets you run and scale code in the cloud with no infra management.

With fal, you can build pipelines, serve ML models and scale them up to many users. You scale down to 0 when you don't use any resources.

Quickstart

First, you need to install the fal package. You can do so using pip:

pip install fal

Then you need to authenticate:

fal auth login

You can also use fal keys that you can get from our dashboard.

Now can use the fal package in your Python scripts as follows:

import fal

@fal.function(
    "virtualenv",
    requirements=["pyjokes"],
)
def tell_joke() -> str:
    import pyjokes

    joke = pyjokes.get_joke()
    return joke

print("Joke from the clouds: ", tell_joke())

A new virtual environment will be created by fal in the cloud and the set of requirements that we passed will be installed as soon as this function is called. From that point on, our code will be executed as if it were running locally, and the joke prepared by the pyjokes library will be returned.

Next steps

If you would like to find out more about the capabilities of fal, check out to the docs. You can learn more about persistent storage, function caches and deploying your functions as API endpoints.

Contributing

Installing in editable mode with dev dependencies

pip install -e 'projects/fal[dev]'
pip install -e 'projects/fal_client[dev]'
pip install -e 'projects/isolate_proto[dev]'

Running tests

pytest

Pre-commit

cd projects/fal
pre-commit install

Commit format

Please follow conventional commits specification for descriptions/messages.

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

fal-1.71.1.tar.gz (1.9 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fal-1.71.1-py3-none-any.whl (236.1 kB view details)

Uploaded Python 3

File details

Details for the file fal-1.71.1.tar.gz.

File metadata

  • Download URL: fal-1.71.1.tar.gz
  • Upload date:
  • Size: 1.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for fal-1.71.1.tar.gz
Algorithm Hash digest
SHA256 e818f5509809a8da6033464a8f50fbc78f26434bc693b0cf887dedaa1135cfe8
MD5 de86c2e64c7e43038cb07c14996a5941
BLAKE2b-256 7ac90ba88e6143fb66bf4e1ff34ab4d7367350ab922792f3d0ddb7d17b2a7644

See more details on using hashes here.

Provenance

The following attestation bundles were made for fal-1.71.1.tar.gz:

Publisher: release.yaml on fal-ai/fal

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file fal-1.71.1-py3-none-any.whl.

File metadata

  • Download URL: fal-1.71.1-py3-none-any.whl
  • Upload date:
  • Size: 236.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for fal-1.71.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4a7af9dab1c3d4a49bee5d6f99be53ba6aef1616ab368374e2431a7c16f7df26
MD5 3ae1f1538ded811d231bbac688a65988
BLAKE2b-256 759944fc1dbdfac50ca5b6a48ecf3357053eae811f1b7eca16f5b0ac0f1459cd

See more details on using hashes here.

Provenance

The following attestation bundles were made for fal-1.71.1-py3-none-any.whl:

Publisher: release.yaml on fal-ai/fal

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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