https://github.com/dtkav/flask-batch

Handle many API calls from a single HTTP request
https://github.com/dtkav/flask-batch

Last synced: 13 days ago
JSON representation

Handle many API calls from a single HTTP request

• Host: GitHub
• URL: https://github.com/dtkav/flask-batch
• Owner: dtkav
• License: mit
• Created: 2018-07-30T07:24:22.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-09-04T07:47:19.000Z (about 6 years ago)
• Last Synced: 2024-07-14T05:02:39.188Z (4 months ago)
• Language: Python
• Homepage:
• Size: 58.6 KB
• Stars: 55
• Watchers: 5
• Forks: 2
• Open Issues: 2
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

Awesome Lists containing this project

README

        
Flask-Batch

===========

|Travis CI build status| |GitHub license| |Latest Version|

*Batch multiple requests at the http layer.* Flask-Batch is inpsired by

`how google cloud storage does

batching `__.

It adds a ``/batch`` route to your API which can execute batched HTTP

requests against your API server side. The client wraps several requests

in a single request using the ``multipart/mixed`` content type.

Installation

============

.. code:: bash

    pip install Flask-Batch

    # to include the dependencies for the batching client

    pip install Flask-Batch[client]

Getting Started

===============

Server

------

.. code:: python

    from flask import Flask

    from flask_batch import add_batch_route

    app = Flask(__name__)

    add_batch_route(app)

    # that's it!

Client

------

The client wraps a requests session.

.. code:: python

    from flask_batch.client import Batching

    import json

    alice_data = bob_data = {"example": "json"}

    with Batching("http://localhost:5000/batch") as s:

        alice = s.patch("/people/alice/", json=alice_data)

        bob = s.patch("/people/bob/", json=bob_data)

    alice         # 

    alice.json()  # {"response": "json"}

Why Batch?

==========

Often the round-trip-time from a client to a server is high. Batching

requests reduces the penalty of a high RTT, without the added complexity

of request parallelization.

.. figure:: sequence-diagram.svg

   :alt: 

Batching Done Right

===================

Often API designers will create custom batch endpoints for specific

operations. Creating custom API endpoints for performing bulk operations

usually end up being clunky. Each one ends up unique. This means more

code to maintain, and more bugs.

It can be difficult to reason about bulk json API endpoints. For

example, what happens on error? Does the bulk operation fail? continue?

roll back?

Batching at the HTTP layer results in clear and expected behaviors that

are easy to reason about. HTTP batching simply behaves the same way as

all of the individual requests that are sent in the batch.

Status

======

This project is in ``alpha``. I'm hoping to eventually get it approved

as a flask extension.

.. |Travis CI build status| image:: https://api.travis-ci.org/dtkav/flask-batch.svg?branch=master

   :target: https://travis-ci.org/dtkav/flask-batch/

.. |GitHub license| image:: https://img.shields.io/github/license/dtkav/flask-batch.svg

   :target: https://github.com/dtkav/flask-batch/blob/master/LICENSE

.. |Latest Version| image:: https://img.shields.io/pypi/v/flask-batch.svg

   :target: https://pypi.python.org/pypi/flask-batch