FastAPI Skeleton App to serve machine learning models production-ready.

Overview

FastAPI Model Server Skeleton

Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramírez](https://github.com/tiangolo).

This repository contains a skeleton app which can be used to speed-up your next machine learning project. The code is fully tested and provides a preconfigured tox to quickly expand this sample code.

To experiment and get a feeling on how to use this skeleton, a sample regression model for house price prediction is included in this project. Follow the installation and setup instructions to run the sample model and serve it aso RESTful API.

Requirements

Python 3.6+

Installation

Install the required packages in your local environment (ideally virtualenv, conda, etc.).

pip install -r requirements

Setup

  1. Duplicate the .env.example file and rename it to .env

  2. In the .env file configure the API_KEY entry. The key is used for authenticating our API.
    A sample API key can be generated using Python REPL:

import uuid
print(str(uuid.uuid4()))

Run It

  1. Start your app with:
uvicorn fastapi_skeleton.main:app
  1. Go to http://localhost:8000/docs.

  2. Click Authorize and enter the API key as created in the Setup step. Authroization

  3. You can use the sample payload from the docs/sample_payload.json file when trying out the house price prediction model using the API. Prediction with example payload

Run Tests

If you're not using tox, please install with:

pip install tox

Run your tests with:

tox

This runs tests and coverage for Python 3.6 and Flake8, Autopep8, Bandit.

Issues
  • Bump uvicorn from 0.11.2 to 0.11.7

    Bump uvicorn from 0.11.2 to 0.11.7

    Bumps uvicorn from 0.11.2 to 0.11.7.

    Release notes

    Sourced from uvicorn's releases.

    Version 0.11.7

    0.11.7

    • SECURITY FIX: Prevent sending invalid HTTP header names and values.
    • SECURITY FIX: Ensure path value is escaped before logging to the console.

    Version 0.11.6

    • Fix overriding the root logger.

    Version 0.11.5

    • Revert "Watch all files, not just .py" due to unexpected side effects.
    • Revert "Pass through gunicorn timeout config." due to unexpected side effects.

    Version 0.11.4

    • Use watchgod, if installed, for watching code changes.
    • Reload application when any files in watched directories change, not just .py files.
    Changelog

    Sourced from uvicorn's changelog.

    0.11.7

    • SECURITY FIX: Prevent sending invalid HTTP header names and values.
    • SECURITY FIX: Ensure path value is escaped before logging to the console.

    0.11.6

    • Fix overriding the root logger.

    0.11.5

    • Revert "Watch all files, not just .py" due to unexpected side effects.
    • Revert "Pass through gunicorn timeout config." due to unexpected side effects.

    0.11.4

    • Use watchgod, if installed, for watching code changes.
    • Watch all files, not just .py.
    • Pass through gunicorn timeout config.

    0.11.3

    • Update dependencies.
    Commits

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    dependencies 
    opened by dependabot[bot] 0
  • 📝 Updated link in README to not display '['

    📝 Updated link in README to not display '['

    It appeared the link was meant to be the github user and not the repo itself. I'm not sure the formatting you wanted, but I'm proposing fixing what I thought was a typo.

    Cheers, I like your skeleton 🎉; thanks for sharing ☺

    opened by icancclearynow 0
  • Bump fastapi from 0.48.0 to 0.65.2

    Bump fastapi from 0.48.0 to 0.65.2

    Bumps fastapi from 0.48.0 to 0.65.2.

    Release notes

    Sourced from fastapi's releases.

    0.65.2

    Security fixes

    This change fixes a CSRF security vulnerability when using cookies for authentication in path operations with JSON payloads sent by browsers.

    In versions lower than 0.65.2, FastAPI would try to read the request payload as JSON even if the content-type header sent was not set to application/json or a compatible JSON media type (e.g. application/geo+json).

    So, a request with a content type of text/plain containing JSON data would be accepted and the JSON data would be extracted.

    But requests with content type text/plain are exempt from CORS preflights, for being considered Simple requests. So, the browser would execute them right away including cookies, and the text content could be a JSON string that would be parsed and accepted by the FastAPI application.

    See CVE-2021-32677 for more details.

    Thanks to Dima Boger for the security report! 🙇🔒

    Internal

    0.65.1

    Security fixes

    0.65.0

    Breaking Changes - Upgrade

    • ⬆️ Upgrade Starlette to 0.14.2, including internal UJSONResponse migrated from Starlette. This includes several bug fixes and features from Starlette. PR #2335 by @​hanneskuettner.

    Translations

    Internal

    0.64.0

    Features

    ... (truncated)

    Commits

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    • @dependabot rebase will rebase this PR
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    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
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    dependencies 
    opened by dependabot[bot] 0
  • Sharing model among worker process

    Sharing model among worker process

    It is a question rather than an issue. I have gone over your code to see if there is a solution to share the model (nlp, prediction etc..) among worker processes to prevent load model for every worker and utilize async definition (which is another subject/problem) but could not see a solution. Is there something you can advice or apply in this skeleton?

    Thanks.

    question 
    opened by mehmetilker 4
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